Evidence Hub

Global prevalence of COPD-OSA overlap syndrome: A systematic review and meta-analysis

Li H, Yang J, Xiao Q, Li M, Pei J, Wang M, Li S

Sleep medicine, 2025

1,871,071 participants · 5 citations

Abstract

Background: COPD-OSA overlap syndrome is an important and prevalent condition. Patients with the overlap syndrome experience more severe respiratory symptoms and worse quality of life, and the relative risk of exacerbations is higher than in either condition alone. Because prevalence estimates of COPD-OSA overlap syndrome vary substantially across studies, there is still no consensus on its exact global prevalence. This review specifically aims to offer a comprehensive overview of the global prevalence of the COPD-OSA overlap syndrome.

Methods: Embase, PubMed, Web of Science, Cochrane and Ovid Medline databases were systematically searched for studies reporting the prevalence of COPD-OSA overlap syndrome published from database inception until February 24, 2025. Random effects meta-analysis was performed using R software. Heterogeneity among the studies was evaluated using the I2 index. Sensitivity analysis, subgroup analysis and meta-regression was conducted to evaluate the heterogeneity source of the results. Begg test was used to assess publication bias.

Results: A total of 41 studies involving 1,871,071 participants were included in this analysis. The global prevalence of COPD-OSA overlap syndrome was 28.3 % (95 % CI: 20.8-36.4 %). Subgroup analysis revealed that the prevalence was higher in cross-sectional studies (30.66 %, 95 % CI: 21.66 %-40.47 %) compared with cohort studies (21.24 %, 95 % CI: 9.74 %-35.69 %). Among continents, Asia exhibited the highest prevalence…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,871,071 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free